CHEM 750/7500-01 - Topics in Computational Chemistry

Semester: Winter 2024

Professor: L. Chen | Discipline: Physical | Campus: Guelph

Description

This course will cover a variety of topics in computational chemistry. Molecular simulation: molecular dynamics in various ensembles, Monte Carlo. Extracting properties from simulations: free energy, dynamical properties from time-correlation functions. Electronic structure theory: Hartree-Fock, density functional theory.

Materials

These textbooks have been placed on reserve through the University of Guelph McLaughlin Library. Please click on each link to receive access to the electronic version, you will need to authenticate with your UofG Central Login Account. For Waterloo students, please contact your library for access to these materials.

Statistical Mechanics: Theory and Molecular Simulation
M. Tuckerman

Understanding Molecular Simulation: From Algorithms to Applications
D. Frenkel and B. Smit

The Art of Molecular Dynamics Simulation
D.C. Rapaport

Density Functional Theory: A Practical Introduction
D. Scholl and J. A. Steckel

Other Useful Texts

Allen and Tildesley, Computer Simulation of Liquids
Haile, Molecular Dynamics Simulations: Elementary Methods
Landau and Binder, A Guide to Monte Carlo Simulations in Statistical Physics
McQuarrie, Statistical Mechanics
Newman and Barkema, Monte Carlo Methods in Statistical Physics

Evaluation

Problem Sets: 40% (4 total, 10% each)

Project Proposal: 25%

Final Project: 35%

Note: All work is to be turned in by 23:59 electronically via email to [email protected] on each due date. Late assignments will be penalized at a rate of 20% of the assignment (Problem Sets and Project Proposal/Final Project) grade per day. Students may work on their Project Proposal/Final Project collaboratively (in pairs) or independently.

Lab/Project

The Problem Sets consist of a combination of theoretical and practical exercises. Students will work with mathematical expressions, writing short scripts in Python, running simulations in different software such as Gaussian and the Atomic Simulation Environment.

To begin your Project Proposal, start by choosing a problem in science that you find particularly interesting and that can be addressed (at least in part) with molecular simulation. Bear in mind that your topic can fall under the umbrella of classical simulation (Monte Carlo/molecular dynamics), electronic structure theory, or simulation and sampling methods. You can propose to complete your calculations on any reasonable simulation platform, including Python, Gaussian, and software compatible with the Atomic Simulation Environment. If you choose to use a simulation platform other than those listed here, note that I will likely be able to offer you little assistance in debugging simulation issues. You are encouraged to choose a topic that has relevance to your current research. Do not, however, propose a simulation project that you’ve already begun/finished in the course of your own research.

Your finished proposal should be 4–6 pages in length, and comprises these five sections:

  1. Introduction (~1.5 pages): Discuss the background associated with your chosen topic along with its relationship to methods in molecular simulation. In particular, note any previous simulation work that has been conducted on or is related to your system. Motivate your proposed work in the context of open/unanswered questions in a field related to your topic of investigation.
  2. Simulation Methodology (~1 page): With your proposed work in mind, describe the simulation and sampling methods you plan to use to complete your calculations. Include any relevant equations, and frame your discussion through the lens of methodology you’ve learned about in class.
  3. Proposed Work (~1 page): Detail the nature of your proposed work. Keep in mind that your proposal can extend beyond the bounds of what you reasonably expect to complete; the focus should be on suggesting a simulation or set of simulations that have the potential to answer an interesting question related to your topic.
  4. Practical Considerations (~1 page): Provided you don’t have access to greater computational resources, it’s likely that you’ll need to complete your proposed simulation on a High-Performance Computing cluster. With this limitation in mind, comment on whether or not you think your proposed work is too ambitious to be completed for your simulation report (perfectly acceptable if the proposal is of a much greater scope). Suggest a reasonable portion/aspect of your proposal that you think you can address over the course of two weeks. Set a goal for the work you’ll include in your simulation report.
  5. References: Include at least 6 (you will likely have many more) references from books or peer-reviewed journals that are relevant to your proposed work.

Example: Suppose you’re interested in conducting a QM/MM simulation of the active site in a given enzyme. Your overarching proposal might involve collecting dynamical trajectories for the full protein, treating catalytic residues in the enzyme at some level of quantum mechanics or density functional theory. Due to the scope and size of the system, a simulation would be impractical to complete in such a short time frame. Your “practical” simulation, therefore, might involve something on the scale of calculating the dissociation energy for some amino acid proton that’s present in your enzyme’s catalytic site. In broad terms, choose something that’s simple but still has relevance to your proposed work.

For your Final Project in this course, you will submit a report detailing the results derived from your proposed simulation work. Your report will be evaluated based on the soundness of the computational ideas you employed in your project, and to a lesser extent, on how well your results align with your Project Proposal. As previously mentioned, the degree to which you are expected to complete your proposed work will be tempered by the limited time and resources you have been given to carry out your calculations. There is no rigorous length requirement placed on your simulation report; you are expected, however, to present your results thoroughly and thoughtfully. Realistically, your report should be at least 3 pages in length, but most likely longer, and contain the following sections:

  1. Simulation Methodology: Describe the simulation protocol you actually followed in deriving your results. This description should be targeted less at the detailed methodological background you provided in your proposal, but more so at the systematic procedure you used to complete your calculations. Provide sample input files along with any simulation code you authored, and, if possible, include an illustration of your simulated system.
  2. Simulation Results: Present the results you obtained from your simulation efforts. Include any relevant numerical data along with figures that illustrate your data.
  3. Discussion and Conclusion: Discuss the scientific implications of your results, and frame your findings in the context of your Project Proposal and previous work in the computational literature. Indicate what you think is your most interesting or important result. If you did not make significant progress toward completing your proposed work, provide an explanation as to why you could not do so. Based on your findings, what future work might you hypothetically conduct to further develop your topic?
  4. References: If you used any previously published simulation code in your calculations, or needed to access additional information not cited in your Project Proposal for this assignment, please include supplementary reference information at the end of your report.

The following table will be updated once the schedule is released

Assessment Assigned Date Due Date
Problem Set 1 September 22, 2021 October 6, 2021
Problem Set 2 October 6, 2021 October 20, 2021
Project Proposal September 13, 2021 October 27, 2021
Problem Set 3 November 3, 2021 November 17, 2021
Problem Set 4 November 17, 2021 December 1, 2021
Final Project September 13, 2021 December 10, 2021

 Labs

There is no lab component in this course.

Schedule

To be announced.

Schedule

  • Tue: 7:00 pm - 9:20 pm in Remote

Office Hours

By appointment: [email protected]